(B) The antibiotics tested are organized by genera. GDC-0973 research buy Concentrations of the antibiotics were: AMP – ampicillin 100 μg mL-1, CAM – chloramphenicol 5 μg mL-1, KAN – kanamycin 1 μg mL-1, MER – meropenem 0.3 μg mL-1, NOR – norfloxacine 0.5 μg mL-1 and TET – tetracycline 5 μg mL-1. Table 1 Antibiotic resistance differences between 3 OTUs of Chryseobacterium (p-values according to Welch Two Sample t-test)   A vs B A vs C B vs C Ampicillin 0.7901

3.24E-15 1.05E-06 Meropenem 0.9101 1.15E-05 6.50E-04 Norfloxacin 0.3138 2.78E-06 0.0052 Tetracycline 0.1027 0.1219 0.011 Chloramphenicol 0.3386 0.374 0.8194 Kanamycin 0.5435 0.121 0.7245 We found that with every antibiotic some genera were almost completely resistant to the drug (Aeromonas to ampicillin), whereas others were quite sensitive (Flavobacterium to ampicillin; Figure 2A). The only exception was meropenem, where all of the genera characterized had an average resistance value 0.5 or higher. None of the 6 antibiotics was able to inhibit growth of all isolates significantly in any of the phylogenetic groups. When we analyzed the data according to the phylogenetic groups, we found that in every group some antibiotics inhibited most of the isolates and some did not inhibit any (Figure 2B). Therefore, some of the resistance might be determined by the phylogenetic affiliation, probably indicating selleck kinase inhibitor intrinsic resistance mechanisms [4, 40]. Several

genera had an average resistance value of around 0.5 (between 0.3 and 0.7). To evaluate whether these average resistance values were caused by the presence of a mixture of fully resistant and fully sensitive isolates, or whether they were caused by an intermediate resistance of all isolates, we analyzed the resistance see more coefficient distribution within each genus (Figure 3 and Additional file 1 : Figure S1). In all cases there was a wide distribution of resistance values, although in some cases grouping around the lowest and highest values can be observed (for example the Pseudomonas isolates analyzed on tetracycline (Figure 3A)). The highly variable resistance within phylogenetic groups suggests

that acquired resistance is responsible for the phenomenon. Figure 3 Examples of resistance coefficient distributions. Antibiotic abbreviations are as indicated RVX-208 in the legend for Figure 2. The resistance coefficient distributions among the eight most numerous genera on antibiotics where the average resistance value for the genus was between 0.3 and 0.7 are provided as Additional file 1: Figure S1. Distribution of multiresistance Several phylogenetic groups showed a high resistance to more than one antibiotic. This could be due to the existence of “superbugs” that are resistant to many drugs and known to thrive in clinical settings [41]. Alternatively, there might be a random distribution of intrinsic and natural resistance levels.