Development of potent antipseudomonal β-lactams by means of polycarboxylation of aminopenicillins.
Shahinur AkterYohei MigiyamaHiroyasu TsutsukiKatsuhiko OnoChika HamasakiTianli ZhangKenki MiyaoTouya ToyomotoKeiichi YamamotoWaliul IslamTakuro SakagamiHirotaka MatsuiYoshihiro YamaguchiTomohiro SawaPublished in: Microbiology and immunology (2021)
Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen that presents a serious risk to immunosuppressed individuals and other extremely vulnerable patients such as those in intensive care units. The emergence of multidrug-resistant Pseudomonas strains has increased the need for new antipseudomonal agents. In this study, a series of amino group-modified aminopenicillin derivatives was synthesized that have different numbers of carboxyl groups and structurally resemble carboxypenicillin-ureidopenicillin hybrids, and their antipseudomonal activities were evaluated. Among the derivatives synthesized, diethylenetriaminepentaacetic acid (DTPA)-modified amoxicillin (DTPA-Amox) showed potent antipseudomonal activity, not only against the laboratory strain PAO1 but also against clinically isolated Pseudomonas strains that were resistant to piperacillin and carbenicillin. DTPA-Amox had no obvious cytotoxic effects on cultured mammalian cells. In addition, in an in vivo model of leukopenia, DTPA-Amox treatment produced a moderate but statistically significant improvement in the survival of mice with P. aeruginosa strain PAO1 infection. These data suggest that polycarboxylation by DTPA conjugation is an effective approach to enhance antipseudomonal activity of aminopenicillins.
Keyphrases
- multidrug resistant
- gram negative
- pseudomonas aeruginosa
- acinetobacter baumannii
- drug resistant
- escherichia coli
- intensive care unit
- end stage renal disease
- biofilm formation
- ejection fraction
- chronic kidney disease
- newly diagnosed
- prognostic factors
- cystic fibrosis
- endothelial cells
- type diabetes
- electronic health record
- staphylococcus aureus
- adipose tissue
- big data
- artificial intelligence
- machine learning
- mechanical ventilation
- data analysis
- patient reported