PBP Target Profiling by β-Lactam and β-Lactamase Inhibitors in Intact Pseudomonas aeruginosa: Effects of the Intrinsic and Acquired Resistance Determinants on the Periplasmic Drug Availability.
PBP Target Profiling by β-Lactam and β-Lactamase Inhibitors in Intact Pseudomonas aeruginosa: Effects of the Intrinsic and Acquired Resistance Determinants on the Periplasmic Drug Availability.
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DOI：
10.1128/spectrum.03038-22
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发表时间：
2023-02-14
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
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缺乏针对铜绿假单胞菌的有效治疗方案是造成无声大流行的主要原因之一。由于靶位点渗透、外排或 β-内酰胺酶水解不良，许多抗生素对耐药菌株无效。需要设计优化抗菌疗法和支持转化药物开发的关键见解。在目前的工作中，我们分析了铜绿假单胞菌 PAO1 中 11 种结构不同的 β-内酰胺和 4 种 β-内酰胺酶抑制剂 (BLI) 的周质药物摄取和与 PBP 的结合。还评估了最普遍的 β-内酰胺耐药机制对 MIC 和周质目标实现的贡献。将细菌培养物 (6.5 log10 CFU/mL) 暴露于每种抗生素的 1/2× PAO1 MIC 30 分钟。未结合的 PBP 用 Bocillin FL 标记并使用 FluorImager 进行分析。亚胺培南广泛灭活所有靶标。头孢菌素优先靶向 PBP1a 和 PBP3。氨曲南和氨地西林分别仅与 PBP3 以及 PBP2 和 PBP4 结合。青霉素优先与 PBP1a、PBP1b 和 PBP3 结合。 BLI 显示 PBP 占用率较差。 oprD 失活会导致亚胺培南目标达到率显着降低，而其他碳青霉烯类药物的影响程度较小。在 oprM 失活后，观察到广泛使用的抗假单胞菌青霉素、头孢菌素、美罗培南、氨曲南和氨地西林的主要靶标的 PBP 占有率有所改善，与 MIC 变化一致。 AmpC 组成型过度表达导致青霉素、头孢菌素和氨曲南的 PBP 占据显着减少。这项工作中获得的数据将支持针对耐药铜绿假单胞菌感染的优化的基于 β-内酰胺的联合疗法的合理设计。重要性 革兰氏阴性病原体中日益严重的抗生素耐药性问题与三个关键方面有关：(i) 多重耐药 (MDR)、广泛耐药 (XDR) 和全耐药 (PDR) 革兰氏阴性菌株在全球范围内的流行蔓延，(ii) 针对多重耐药菌株的有效新抗生素数量减少，以及 (iii) 缺乏合理的组合和剂量策略。我们的共同努力不仅应该集中于新抗菌药物的开发，还应该集中于将这些药物与临床上现有的其他药物结合使用。我们的工作在分子水平上确定了这些化合物在临床相关细菌铜绿假单胞菌中的有效性，评估了净流入率及其接近目标并实现细菌杀灭而不产生耐药性的能力。这项工作产生的数据将有助于转化药物的开发。
The lack of effective treatment options against Pseudomonas aeruginosa is one of the main contributors to the silent pandemic. Many antibiotics are ineffective against resistant isolates due to poor target site penetration, efflux, or β-lactamase hydrolysis. Critical insights to design optimized antimicrobial therapies and support translational drug development are needed. In the present work, we analyzed the periplasmic drug uptake and binding to PBPs of 11 structurally different β-lactams and 4 β-lactamase inhibitors (BLIs) in P. aeruginosa PAO1. The contribution of the most prevalent β-lactam resistance mechanisms to MIC and periplasmic target attainment was also assessed. Bacterial cultures (6.5 log10 CFU/mL) were exposed to 1/2× PAO1 MIC of each antibiotic for 30 min. Unbound PBPs were labeled with Bocillin FL and analyzed using a FluorImager. Imipenem extensively inactivated all targets. Cephalosporins preferentially targeted PBP1a and PBP3. Aztreonam and amdinocillin bound exclusively to PBP3 and to PBP2 and PBP4, respectively. Penicillins bound preferentially to PBP1a, PBP1b, and PBP3. BLIs displayed poor PBP occupancy. Inactivation of oprD elicited a notable reduction of imipenem target attainment, and it was to a lesser extent in the other carbapenems. Improved PBP occupancy was observed for the main targets of the widely used antipseudomonal penicillins, cephalosporins, meropenem, aztreonam, and amdinocillin upon oprM inactivation, in line with MIC changes. AmpC constitutive hyperexpression caused a substantial PBP occupancy reduction for the penicillins, cephalosporins, and aztreonam. Data obtained in this work will support the rational design of optimized β-lactam-based combination therapies against resistant P. aeruginosa infections. IMPORTANCE The growing problem of antibiotic resistance in Gram-negative pathogens is linked to three key aspects, (i) the progressive worldwide epidemic spread of multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) Gram-negative strains, (ii) a decrease in the number of effective new antibiotics against multiresistant isolates, and (iii) the lack of mechanistically informed combinations and dosing strategies. Our combined efforts should focus not only on the development of new antimicrobial agents but the adequate administration of these in combination with other agents currently available in the clinic. Our work determined the effectiveness of these compounds in the clinically relevant bacteria Pseudomonas aeruginosa at the molecular level, assessing the net influx rate and their ability to access their targets and achieve bacterial killing without generating resistance. The data generated in this work will be helpful for translational drug development.
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影响因子：
6.7
作者：
Lang, Yinzhi;Shah, Nirav R.;Tao, Xun;Reeve, Stephanie M.;Zhou, Jieqiang;Moya, Bartolome;Sayed, Alaa R. M.;Dharuman, Suresh;Oyer, Jeremiah L.;Copik, Alicja J.;Fleischer, Brett A.;Shin, Eunjeong;Werkman, Carolin;Basso, Kari B.;Deveson Lucas, Deanna;Sutaria, Dhruvitkumar S.;Megroz, Marianne;Kim, Tae Hwan;Loudon-Hossler, Victoria;Wright, Amy;Jimenez-Nieves, Rossie H.;Wallace, Miranda J.;Cadet, Keisha C.;Jiao, Yuanyuan;Boyce, John D.;LoVullo, Eric D.;Schweizer, Herbert P.;Bonomo, Robert A.;Bharatham, Nagakumar;Tsuji, Brian T.;Landersdorfer, Cornelia B.;Norris, Michael H.;Soo Shin, Beom;Louie, Arnold;Balasubramanian, Venkataraman;Lee, Richard E.;Drusano, George L.;Bulitta, Juergen B.
通讯作者：
Bulitta, Juergen B.
影响因子：
4.9
作者：
LIVERMORE, DM;DAVY, KWM
通讯作者：
DAVY, KWM
影响因子：
5.2
作者：
LIVERMORE, DM
通讯作者：
LIVERMORE, DM
影响因子：
3.2
作者：
Dougherty, TJ;Kennedy, K;Pucci, MJ
通讯作者：
Pucci, MJ
影响因子：
5.2
作者：
Livermore, DM;Mushtaq, S;Warner, M
通讯作者：
Warner, M