β-lactamase-resistant bacteria (Phaeno Thera)

Pathogens producing β-lactamase pose a great challenge to antibiotic-resistant infection treatment; thus, it is urgent to discover novel β-lactamase inhibitors for drug development. Conventional high-throughput screening is very costly, and structure-based virtual screening is limited with mechanisms. In this study, we construct a novel multichannel deep neural network (DeepBLI) for β-lactamase inhibitor screening, pretrained with a label reversal KIBA data set and fine-tuned on β-lactamase-inhibitor pairs from BindingDB. First, the pairs of encoders (Conv and Att) fuse the information spatially and sequentially for both enzymes and inhibitors. Then, a co-attention module creates the connection between the inhibitor and enzyme embeddings. Finally, multichannel outputs fuse with an element-wise product and then are fed into 3-layer fully connected networks to predict interactions. Comparing the state-of-the-art methods, DeepBLI yields an AUROC of 0.9240 and an AUPRC of 0.9715, which indicates that it can identify new β-lactamase-inhibitor interactions. To demonstrate its prediction ability, an application of DeepBLI is described to screen potential inhibitor compounds for metallo-β-lactamase AIM-1 and repurpose rottlerin for four classes of β-lactamase targets, showing the possibility of being a broad-spectrum inhibitor. DeepBLI provides an effective way for antibacterial drug development, contributing to antibiotic-resistant therapeutics.

Chryseobacterium indologenes (C. indologenes) has recently emerged as a cause of life-threatening nosocomial infections in humans. This study aims to investigate the clinical characteristics, homology, and antimicrobial patterns of C. indologenes clinical isolates at a teaching hospital in Shanghai, China.

A total of 135 consecutive non-replicate clinical C. indologenes isolates from January 2010 to December 2018 were collected at a tertiary care university hospital in Shanghai, China. Genetic relatedness of the isolates was performed by pulsed-field gel electrophoresis (PFGE). The antimicrobial susceptibility of these isolates was measured by the microdilution broth method. The prevalence of β-lactamase genes was investigated by polymerase chain reaction (PCR), while the quinolone resistance-determining regions (QRDRs) were sequenced.

All 135 C. indologenes isolates were collected from hospitalized patients with an average age of 55 years. Most of these clinical isolates were derived from ascites (59.3%) or urine (23.7%) specimens. Eighty (80/135) of the strains were classified as clone D by PFGE. In vitro drug susceptibility tests showed that minocycline and trimethoprim-sulfamethoxazole had sound antibacterial effects. However, more than 86% of the tested strains were resistant to cephalosporins (ceftazidime, cefotaxime), β-lactamase/β-lactamase inhibitors (cefoperazone-sulbactam), and carbapenems (meropenem, imipenem). Metallo-β-lactamase bla _IND and type A broad-spectrum β-lactamase genes bla _CIA were present in 135 and 103 isolates, respectively. The clinical strains in our hospital mainly carried bla _IND-2 (89.6%, 121/135). Compared with previous studies, these strains had a high rate of resistance to quinolones. The resistance rates to levofloxacin, ciprofloxacin, norfloxacin, gatifloxacin, and nemonoxacin were as high as 83.7-94.8%. The mutations at Ser83Val, Ser83Tyr, and Asp87Gly in the QRDRs of GyrA were significantly related to the resistance of C. indologenes to levofloxacin. All but one quinolone-resistant strain contained at least one significant mutation.

This study showed a clonal dissemination of C. indologenes isolates in infections at a tertiary care university hospital in Shanghai, China. Minocycline and trimethoprim-sulfamethoxazole had favorable in vitro antibacterial effects. However, the high resistance rate to β-lactams and quinolones was due to carrying β-lactamase (bla _IND, bla _CIA), and mutations in the QRDRs of GyrA.