Antibiotic poly-resistance (multidrug-, extreme-, and pan-drug resistance) is controlled by adaptive evolution. Darwinian and Lamarckian interpretations of resistance evolution are discussed. Arguments for, and against, pessimistic forecasts on a fatal “post-antibiotic era” are evaluated. In commensal niches, the appearance of a new antibiotic resistance often reduces fitness, but compensatory mutations may counteract this tendency. The appearance of new antibiotic resistance is frequently accompanied by a collateral sensitivity to other resistances. Organisms with an expanding open pan-genome, such as Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae, can withstand an increased number of resistances by exploiting their evolutionary plasticity and disseminating clonally or poly-clonally. Multidrug-resistant pathogen clones can become predominant under antibiotic stress conditions but, under the influence of negative frequency-dependent selection, are prevented from rising to dominance in a population in a commensal niche. Antimicrobial peptides have a great potential to combat multidrug resistance, since antibiotic-resistant bacteria have shown a high frequency of collateral sensitivity to antimicrobial peptides. In addition, the mobility patterns of antibiotic resistance, and antimicrobial peptide resistance, genes are completely different. The integron trade in commensal niches is fortunately limited by the species-specificity of resistance genes. Hence, we theorize that the suggested post-antibiotic era has not yet come, and indeed might never come.

Quantifying bacteria per unit mass or volume is a common task in various fields of microbiology (e.g., infectiology and food hygiene). Most bacteria can be grown on culture media. The unicellular bacteria reproduce by dividing into two cells, which increases the number of bacteria in the population. Methodologically, this can be followed by culture procedures, which mostly involve determining the number of bacterial colonies on the solid culture media that are visible to the naked eye. However, it is a time-consuming and laborious professional activity. Addressing the automation of colony counting by convolutional neural networks in our work, we have cultured 24 bacteria species of veterinary importance with different concentrations on solid media. A total of 56,865 colonies were annotated manually by bounding boxes on the 369 digital images of bacterial cultures. The published dataset will help developments that use artificial intelligence to automate the counting of bacterial colonies.

While the One Health issues of intensive animal farming are commonly discussed, keeping companion animals is less associated with the interspecies headway of antimicrobial resistance. With the constant advance in veterinary standards, antibiotics are regularly applied in companion animal medicine. Due to the close coexistence of dogs and humans, dog bites and other casual encounters with dog saliva (e.g., licking the owner) are common. According to our metagenome study, based on 26 new generation sequencing canine saliva datasets from 2020 and 2021 reposited in NCBI SRA by The 10,000 Dog Genome Consortium and the Broad Institute within Darwin’s Ark project, canine saliva is rich in bacteria with predictably transferable antimicrobial resistance genes (ARGs). In the genome of potentially pathogenic Bacteroides, Capnocytophaga, Corynebacterium, Fusobacterium, Pasteurella, Porphyromonas, Staphylococcus and Streptococcus species, which are some of the most relevant bacteria in dog bite infections, ARGs against aminoglycosides, carbapenems, cephalosporins, glycylcyclines, lincosamides, macrolides, oxazolidinone, penams, phenicols, pleuromutilins, streptogramins, sulfonamides and tetracyclines could be identified. Several ARGs, including ones against amoxicillin–clavulanate, the most commonly applied antimicrobial agent for dog bites, were predicted to be potentially transferable based on their association with mobile genetic elements (e.g., plasmids, prophages and integrated mobile genetic elements). According to our findings, canine saliva may be a source of transfer for ARG-rich bacteria that can either colonize the human body or transport ARGs to the host bacteriota, and thus can be considered as a risk in the spread of antimicrobial resistance.

Florfenicol is a member of the phenicol group, a broad-spectrum antibacterial agent. It has been used for a long time in veterinary medicine, but there are some factors regarding its pharmacokinetic characteristics that have yet to be elucidated. The aim of our study was to describe the pharmacokinetic profile of florfenicol in synovial fluid and plasma of swine after intramuscular (i.m.) administration. In addition, the dosage regimen of treatment of arthritis caused by S. suis was computed for florfenicol using pharmacokinetic/pharmacodynamic (PK/PD) indices. As the first part of our investigation, the pharmacokinetic (PK) parameters of florfenicol were determined in the plasma and synovial fluid of six pigs. Following drug administration (15 mg/kg_bw, intramuscularly), blood was drawn at the following times: 10, 20, 30, 40, 50 and 60 min, 2, 3, 4, 5, 6, 7, 8, 12, 24, 48 and 72 h; synovial fluid samples were taken after 1, 2, 3, 4, 6, 8, 12, 24, 48 and 72 h. The concentration of florfenicol was determined by a validated liquid chromatography-mass spectrometry (LC-MS/MS) method via multiple reaction monitoring (MRM) modes. As the second part of our research, minimum inhibitory concentration (MIC) values of florfenicol were determined in 45 S. suis strains isolated from clinical samples collected in Hungary. Furthermore, a strain of S. suis serotype 2 (SS3) was selected, and killing-time curves of different florfenicol concentrations (0.5 µg/mL, 1 µg/mL and 2 µg/mL) were determined against this strain. Peak concentration of the florfenicol was 3.58 ± 1.51 µg/mL in plasma after 1.64 ± 1.74 h, while it was 2.73 ± 1.2 µg/mL in synovial fluid 3.4 ± 1.67 h after administration. The half-life in plasma was found to be 17.24 ± 9.35 h, while in synovial fluid it was 21.01 ± 13.19 h. The area under the curve (AUC_24h) value was 54.66 ± 23.34 μg/mL·h for 24 h in plasma and 31.24 ± 6.82 μg/mL·h for 24 h in synovial fluid. The drug clearance scaled by bioavailability (Cl/F) in plasma and synovial fluid was 0.19 ± 0.08 L/h/kg and 0.29 ± 0.08 L/h/kg, respectively. The mean residence time (MRT) in plasma and synovial fluid was 24.0 ± 13.59 h and 27.39 ± 17.16 h, respectively. The steady-state volume of distribution (V_ss) in plasma was calculated from Cl/F of 0.19 ± 0.08 L/h/kg, multiplied by MRT of 24.0 ± 13.59 h. For the PK/PD integration, average plasma and synovial fluid concentration of florfenicol was used in a steady-state condition. The obtained MIC₅₀ value of the strains was 2.0 µg/mL, and MIC₉₀ proved to be 16.0 µg/mL. PK/PD integration was performed considering AUC_24h/MIC breakpoints that have already been described. This study is the first presentation of the pharmacokinetic behavior of florfenicol in swine synovia as well as a recommendation of extrapolated critical MICs of S. suis for therapeutic success in the treatment of S. suis arthritis in swine, but it should be noted that this requires a different dosage regimen to that used in authorized florfenicol formulations.

A total of 114 Actinobacillus pleuropneumoniae isolates from porcine hemorrhagic necrotic pleuropneumonia were characterized by the examination of biotype, serovar, antibiotic resistance genes, and genes of toxin production. Pulsed-field gel electrophoresis was used to analyze their genetic relationship, which identified 16 clusters. Serovar 2 (50 isolates), serovar 13 (25 isolates), serovar 9 (11 isolates), and serovar 16 (7 isolates) were the most frequent serovars. Serovar 2 formed nine distinguishable clusters; serovar 13 and serovar 16 were less diverse, exhibiting two potentially related subclusters; serovar 9 was represented by a single cluster. Remarkably small differences were seen in the core genome when nine representative isolates of serovar 13 were subjected to whole-genome sequencing. Tetracycline resistance was relatively frequent in the two clusters of serovar 13; one of them was also frequently resistant against beta-lactams. Resistance in other serovars was sporadic. All isolates carried the apxIV gene. The toxin profiles of serovar 2 were characterized by the production of ApxII and ApxIII toxins, except for a small cluster of three isolates: serovar 9 and serovar 16 isolates produced ApxI and ApxII toxins. Serovar 13 carried apxII and apxIBD genes, indicating the production of the ApxII toxin, but not of ApxI or ApxIII. The unusually high frequency and low diversity of serovar 13 are not explained by its virulence properties, but the high frequency of resistance to beta-lactams and tetracyclines may have played a role in its spread. The emergence of serovar 16 may be facilitated by its high virulence, also explaining its high clonality.

Porcine respiratory disease complex (PRDC) has been a major animal health, welfare, and economic problem in Hungary; therefore, great emphasis should be put on both the prevention and control of this complex disease. As antibacterial agents are effective tools for control, antibiotic susceptibility testing is indispensable for the proper implementation of antibacterial therapy and to prevent the spread of resistance. The best method for this is to determine the minimum inhibitory concentration (MIC) by the broth microdilution method. In our study, we measured the MIC values of 164 Actinobacillus pleuropneumoniae, 65 Pasteurella multocida, and 118 Streptococcus suis isolates isolated from clinical cases against the following antibacterial agents: amoxicillin, ceftiofur, cefquinome, oxytetracycline, doxycycline, tylosin, tilmicosin, tylvalosin, tulathromycin, lincomycin, tiamulin, florfenicol, colistin, enrofloxacin, and sulfamethoxazole-trimethoprim. Outstanding efficacy against A. pleuropneumoniae isolates was observed with ceftiofur (100%) and tulathromycin (100%), while high levels of resistance were observed against cefquinome (92.7%) and sulfamethoxazole-trimethoprim (90.8%). Ceftiofur (98.4%), enrofloxacin (100%), florfenicol (100%), and tulathromycin (100%) were found to be highly effective against P. multocida isolates, while 100% resistance was detected against the sulfamethoxazole-trimethoprim combination. For the S. suis isolates, only ceftiofur (100%) was not found to be resistant, while the highest rate of resistance was observed against the sulfamethoxazole-trimethoprim combination (94.3%). An increasing number of studies report multi-resistant strains of all three pathogens, making their monitoring a high priority for animal and public health.